The spread spectrum communication system is widely used nowadays. The spread spectrum or the pseudo-random (PN) code modulation can decrease the interference from other users and wireless signals. During the cross-correlation process of received signals and PN sequence, when the interference is a narrow-band signal, the interference, signals will spread to the entire band and thus weaken the impact of the interference. As a result, the spread spectrum signals could weaken the narrow-band interference to some extend.
The typical spectrum of a spread spectrum signal (e.g. performing spread spectrum from PN sequence) is submerged in the noise, as shown in FIG. 1. Ideal signal is the signal energy that is actually sent out by the mobile station and noise is the additive interference. Obviously, the ideal signal energy of the spread spectrum is usually less than the noise energy. The “strong interference” generally refers to the blocking signals or the signals that are sent out by TV, wireless station and nearby communication equipments. “Typical interference” refers to the signals sent out by those low-power sources, such as amateur radio. Processing gain represents the level of the interference signals tolerable by the spread signals in mobile station. The spread signals can still be recovered when they are affected by the typical interference, but they will never be recovered when the strong interference shows up. What's more, even with the typical interference, the system performance will degrade thought the signals can be recovered.
Before utilizing CDMA communication system, the frequency band will be swept in order to protect the CDMA signals from the interference of narrow-band signals. However, since some burst signals are hard to be fully forbidden due to their burst characteristics, the narrow-band interference will present disorder and randomicity. The narrow-band interference will increase the congestion rate and call-dropping rate in a CDMA system, overload the radio-frequency power control system, increase the power consumption of mobile station and reduce the base station coverage. Under extreme situation, the high-power interference will even block the entire cell, and thus the normal communication will stop. As a result, a good solution have to be found in order to eliminate the impact of the narrow-band interference signals on the CDMA signals and guarantee good quality of the communication.
Generally, methods for dealing with narrow-band interference are divided into two categories:
The first category is to make the signal (usually under analog processing) pass through a narrow-band notch filter or filter group. This method is usually realized by the surface acoustic technology, in which the estimation for the frequency of interference signals is made and based on the estimation result, a narrow-band notch filter is placed where there are interference signals (the PLL (phase locked loop) can also be used to track the interference signals). However, the analog technology has its own limitations, and usually lacks flexibility.
Another kind of methods is frequency domain elimination which is generally realized through digital processing. Signals are first digitized and then transformed into frequency domain through Fourier Transform. These data will be processed in the frequency domain and finally be transformed back into the time domain to be output through inverse-Fourier Transform. The methods for processing interference signals in the frequency domain can be summarized into two types: the first one is to filter out the interference impact through the filter on the frequency domain data and this method is suitable when the bandwidth and location of the interference are already known, but this method will have a certain limitation when the interference location in the frequency domain, the bandwidth and the number of the interferences are hard to identify, since there is a certain degree of difficulty in designing a fully adaptive filter.
Another type is to compute the signal amplitude on each frequency point and then compares them with the threshold value. Signals exceeding the threshold values are considered as narrow-band interference signals and will be set as zero or be degraded to noise level. This method could adaptively process multiple interference, multiple interference bandwidths and interference frequency changes, but whether the threshold setting in this method is good or not will directly affect its performance. The common way of setting threshold is to calculate the average value of the energies or amplitudes of all the data that are transformed into frequency domain and multiply that average value with a fixed multiple, so the computed average value will be the main criteria in setting up the threshold. This method of setting threshold value will be subject to the impacts of the magnitude and the number of narrow-band interferences, because the obtained average value will have a corresponding increase when the energy and the number of the narrow-band interferences increase. Therefore it can not reflect the real performance of the energy of non-interference data and decrease the performance in interference suppression.